What is the relation between estimator and estimate?
Feb 24, 2011 · In Lehmann's formulation, almost any formula can be an estimator of almost any property. There is no inherent mathematical link between an estimator and an estimand. However, …
What is the difference between an estimator and a statistic?
An "estimator" or "point estimate" is a statistic (that is, a function of the data) that is used to infer the value of an unknown parameter in a statistical model. So a statistic refers to the data itself and a …
bias - Example of a biased estimator? - Cross Validated
Dec 15, 2020 · Currently very confused in my stats class about what a biased estimator is. Does anyone know of a good and simple example of one that's easy to understand why it's biased and how to …
random variable - When is the median-of-means estimator better than …
May 22, 2023 · When is the median-of-means estimator better than the standard mean? Ask Question Asked 2 years, 7 months ago Modified 2 years, 1 month ago
What is the difference between a consistent estimator and an unbiased ...
An estimator is unbiased if, on average, it hits the true parameter value. That is, the mean of the sampling distribution of the estimator is equal to the true parameter value.
bias - How does one explain what an unbiased estimator is to a ...
Sep 22, 2016 · 15 Suppose $\hat {\theta}$ is an unbiased estimator for $\theta$. Then of course, $\mathbb {E} [\hat {\theta} \mid \theta] = \theta$. How does one explain this to a layperson? In the …
Notation in statistics (parameter/estimator/estimate)
Aug 2, 2018 · We use an estimator which books usually denote by ˆθ. The estimator is a random variable! Usually we seek E[ˆθ] = θ and so on and on, anyways. An estimate is the value we obtain …
Estimator for a binomial distribution - Cross Validated
Oct 7, 2011 · For bernoulli I can think of an estimator estimating a parameter p, but for binomial I can't see what parameters to estimate when we have n characterizing the distribution? Update: By an …
Is unbiasedness a necessary condition for an estimator to be efficient?
The term 'an efficient estimator' is typically used for unbiased estimators. To apply it to biased estimators is possible but it requires some bending and reshaping of the definitions.
ML vs WLSMV: which is better for categorical data and why?
I was wondering which is a better estimator to use for categorical data: ML or WLSMV. I saw on a discussion on the Mplus website that they recommend WLSMV for categorical data but didn't explain …